Algorithms are virtually ubiquitous on the internet today, perpetually, visibly or invisibly, shaping the way we use internet services. In fact, they filter the news we read, influence our purchasing decisions, select the music we listen to, or determine our interactions on social media platforms. However, studies indicate that public awareness and understanding of algorithms on the internet remains low among users. This lack of knowledge is problematic, since it increases users' vulnerability, not only on a personal but also at the societal level, as it exposes them to potential forms of manipulation and exploitation by digital service and content providers. The concept of algorithmic literacy has been proposed to describe the specific knowledge and skills required by the internet users to understand how algorithms operate on the internet. The aim of this master’s thesis is to synthesize past research on algorithmic literacy and to provide the Slovenian translation of the Algorithmic Literacy Scale (ALS) for internet users which was developed by Dogruel et al. (2022). The translation of ALS was conducted in line with the Translation, Review, Adjudication, Pretest, and Documentation (TRAPD) model. TRAPD is the state-of-art approach to translation of questionnaires in cross-national surveys. The outcome of this thesis is a culturally and linguistically adapted Slovenian translation of the ALS that scholars can use in future studies on algorithm awareness and knowledge in Slovenia. In addition, the thesis discusses some limitations and specific consideration in the use of the TRAPD approach, that should be accounted for, when using the Slovenian translation of the ALS.
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